Objective Difference Grade Research Articles

Analisis Kinerja Skema MPEG Surround Pada Pengkodean Audio 22 Kanal Menggunakan Bitrate 1000 - 2000 Kbps

MPEG surround is one of the most popular multichannel audio coding standards used today. In producing quality sound, there are several parts that are influential, but those that are directly related to sound reproduction, one of which is the method of downmixing, mixing the right channels will improve the quality of the sound produced. Because this research is closely related to data computing, the Matrix Laboratory (MATLAB) application is used. There are 2 stages carried out in the MATLAB application, namely the encoding and decoding process. In the encoding process in MATLAB, each audio channel is set according to a previously designed scheme. The results of this encoding are then decoded, so that the ODG value of each tested audio channel is obtained. In his presentation, the design and analysis of several domnmixing schemes was carried out. There are 5 schemes tested and to determine the performance of each scheme, these schemes are tested at high bitrates, from the range of 1000 Kbps to 2000 Kbps. Based on the test, it was found that the effect of increasing the bitrate is directly proportional to the resulting audio quality. During testing Scheme-5 has a better level of stability among all downmixing schemes and the average percentage increase in Objective Difference Grade (ODG) for all audio samples is 9.6927 %.

Time-Frequency Phase Retrieval for Audio—The Effect of Transform Parameters

In audio processing applications, phase retrieval (PR) is often performed from the magnitude of short-time Fourier transform (STFT) coefficients. Although PR performance has been observed to depend on the considered STFT parameters and audio data, the extent of this dependence has not been systematically evaluated yet. To address this, we studied the performance of three PR algorithms for various types of audio content and various STFT parameters such as redundancy, time-frequency ratio, and the type of window. The quality of PR was studied in terms of objective difference grade and signal-to-noise ratio of the STFT magnitude, to provide auditory- and signal-based quality assessments. Our results show that PR quality improved with increasing redundancy, with a strong relevance of the time-frequency ratio. The effect of the audio content was smaller but still observable. The effect of the window was only significant for one of the PR algorithms. Interestingly, for a good PR quality, each of the three algorithms required a different set of parameters, demonstrating the relevance of individual parameter sets for a fair comparison across PR algorithms. Based on these results, we developed guidelines for optimizing STFT parameters for a given application.

Dictionary Learning for Sparse Audio Inpainting

The objective of audio inpainting is to fill a gap in an audio signal. This is ideally done by reconstructing the original signal or, at least, by inferring a meaningful surrogate signal. We propose a novel approach applying sparse modeling in the time-frequency (TF) domain. In particular, we devise a dictionary learning technique which learns the dictionary from reliable parts around the gap with the goal to obtain a signal representation with increased TF sparsity. This is based on a basis optimization technique to deform a given Gabor frame such that the sparsity of the analysis coefficients of the resulting frame is maximized. Furthermore, we modify the SParse Audio INpainter (SPAIN) for both the analysis and the synthesis model such that it is able to exploit the increased TF sparsity and—in turn—benefits from dictionary learning. Our experiments demonstrate that the developed methods achieve significant gains in terms of signal-to-distortion ratio (SDR) and objective difference grade (ODG) compared with several state-of-the-art audio inpainting techniques.

A Novel Integrity Authentication Algorithm Based on Perceptual Speech Hash and Learned Dictionaries

Perceptual speech hash and robust watermarking have been widely investigated to solve the problems of authenticating speech integrity. The former generates a watermark and the latter embeds the watermark into the speech signal to implement speech integrity authentication. In this paper, we propose a perceptual speech hash algorithm and a robust watermarking algorithm for speech integrity authentication. To obtain perceptual speech hash values, we propose a gammatone filter model of the speech signal to extract sensitive auditory features (denoted by gammatone features). A random Gaussian matrix is used to reduce the dimensionality of the features of the gammatone to generate perceptual speech hash values. For the watermarking algorithm, we construct learned dictionaries to obtain the robust sparse feature of coefficients of the stationary wavelet transforms, and embed a watermark (perceptual speech hash values) into the sparse feature by patchwork and quantization index modulation. We illustrate the good imperceptibility of the authentication scheme in terms of the signal-to-noise ratio, objective difference grade, and subjective difference grade, and verify its robustness against common signal processing operations while maintaining imperceptibility. Moreover, our proposed method is sensitive to the malicious modification of the watermarked speech. Compared with state-of-the-art algorithms, the proposed algorithm can obtain better comprehensive performance in the detection and localization of tampering with the content of speech.

A Context Encoder For Audio Inpainting

In this article, we study the ability of deep neural networks (DNNs) to restore missing audio content based on its context, i.e., inpaint audio gaps. We focus on a condition which has not received much attention yet: gaps in the range of tens of milliseconds. We propose a DNN structure that is provided with the signal surrounding the gap in the form of time-frequency (TF) coefficients. Two DNNs with either complex-valued TF coefficient output or magnitude TF coefficient output were studied by separately training them on inpainting two types of audio signals (music and musical instruments) having 64-ms long gaps. The magnitude DNN outperformed the complex-valued DNN in terms of signal-to-noise ratios and objective difference grades. Although, for instruments, a reference inpainting obtained through linear predictive coding performed better in both metrics, it performed worse than the magnitude DNN for music. This demonstrates the potential of the magnitude DNN, in particular for inpainting signals that are more complex than single instrument sounds.

Performance Evaluation of Audio Coding by Amalgam AAC and FLAC Audio codec using MDCT and INTMDCT Algorithm

The MDCT and IntMDCT Algorithm is widely utilized is Audio coding.By lifting scheme or rounding operation IntegerMDCT is evolved from Modified Discrete Cosine Transform.This method acquire the properties of MDCT and contribute excelling invertiblity and good spectral mean.In this paper we discuss about the audio codec like AAC and FLAC using MDCT and Integer MDCT algorithm and to find which algorithm shows better Compression Ratio(CR).The confines of this task is to hybriding lossy and lossless audio codec with diminished bit rate but with finer sound quality. Certainly the quality of the audio is figure out by Subjective and Objective testing which is in terms of MOS (Mean opinion square) , ABx and some of the hearing aid testing methodology like PEAQ(Perceptual Evaluation Audio Quality) and ODG(Objective Difference Grade)is followed. Execution measure, that is Compression Ratio(CR) and Sound Pressure Level (SPL) is approximated.

Framework for audio reversible watermarking robust against content replacement with signal restoration capabilities

In the literature, there are robust Reversible Watermarking Schemes (RWS) that allow the extraction of watermarks after the signals have suffered attacks, however the modified carrier signals cannot be restored. On the other hand, self-recovery schemes allow the restoration of the attacked regions of the signals, but the embedding capacity is used for control information, and secret messages cannot be inserted in these type of schemes. In this manuscript a framework for robust reversible watermarking with signal restoration capabilities is proposed. This framework is a general construction that can be followed to implement schemes for different type of media. Previous works that propose a RWS and a self-recovery scheme, both for audio signals, have been taken to construct an implementation of the framework for audio signals. These schemes use the auditory masking properties of audio segments to insert the secret message and the control information required for restoration in a transparent manner. Results obtained with this implementation demonstrate that this construction fulfills a transparency constraint of −2 Objective Difference Grade (ODG) for practical applications, and it reaches payload capacities up to 13 kilobits per second (kbps) with acceptable robustness and adequate quality for the restored signals.

Impulsive spike enhancement on gamelan audio using harmonic percussive separation

Impulsive spikes often occur in audio recording of gamelan where most existing methods reduce it. This research offers new method to enhance audio impulsive spike in gamelan music that is able to reduce, eliminate and even strengthen spikes. The process separates audio components into harmonics and percussive components. Percussion component is set to rise or lowered, and the results of the process combined with harmonic components again. This study proposes a new method that allows reducing, eliminating and even amplifying the spike. From the similarity test using the Cosine Distance method, it is seen that spike enhancement through Harmonic Percussive Source Separation (HPSS) has an average Cosine Distance value of 0.0004 or similar to its original, while Mean Square Error (MSE) has an average value of 0.0004 that is very small in average error and also very similar. From the Perceptual Evaluation of Audio Quality (PEAQ) testing with Harmonic Percussive Source Separation (HPSS), it has a better quality with an average Objective Difference Grade (ODG) of -0.24 or Imperceptible.

A robust digital audio watermarking scheme based on DWT and Schur decomposition

The vulnerability of digital audio signals for different types of risks requires an imperceptible and robust digital audio watermarking scheme. In this research, we propose creating one such imperceptible and robust hybrid watermarking scheme based on a discrete wavelet transform (DWT) and Schur decomposition hybrid method. The proposed scheme embeds the foreground bits of the watermarking image into the least significant bit of the diagonal coefficients of the triangular matrix S generated from Schur decomposition. Schur decomposition is applied on the second sub-band HL2 generated from applying a second-level 2D-Haar DWT on the first channel of the original audio signal. We analyze the proposed digital audio watermarking scheme’s performance in terms of signal to noise ratio (SNR), objective difference grades (ODG), and subjective difference grades (SDG) that resulting 81.43, 4.78 and 0.184, respectively. The resulting of payload capacity, NC, and BER are as high as 319.29 bps, 0.9911, and 0.0135, respectively. Experimental results confirm that the proposed scheme is inaudible and robust against common types of attacks such as Gaussian noise, re-quantization, re-sampling, low-pass filter, high-pass filter, echo, MP3 compression, and cropping. In comparison with state-of-the-art audio watermarking schemes, the proposed scheme’s performance is superior in term of imperceptibility, robustness, and data payload size.

An imperceptible, robust, and high payload capacity audio watermarking scheme based on the DCT transformation and Schur decomposition

This paper proposes a novel audio watermarking scheme based on the discrete cosine transform (DCT) and Schur decomposition. The proposed scheme uses the DCT transformation to increase robustness and the Schur decomposition to achieve perceptual transparency. The proposed scheme first applies the DCT transformation to the original audio signal and then applies the Schur decomposition to the mid-frequency band of the DCT coefficients that generate two matrices (U and S). The watermark bits are embedded into the diagonal elements of the triangular matrix S. The Schur decomposition increases the perceptual transparency and the DCT transformation increases robustness of the proposed audio watermarking scheme by effectively resisting several types of audio signal attacks. The imperceptibility of the proposed watermarking scheme is measured subjectively using subjective difference grades (SDG) and objectively using signal-to-noise ratio (SNR) and objective difference grades (ODG) metrics. Its robustness is evaluated against several types of attacks in terms of NC and BER for different types of audio. The resulting of payload capacity, SNR, NC, and BER are as high as 516.26 bps, 77.95, 0.05326, and 0.9727, respectively. Experimental results confirm the proposed scheme is efficient, imperceptible, and robust with a high payload capacity and no effecting audio signal.

A steganographic approach to hide secret data in digital audio based on XOR operands triplet property with high embedding rate and good quality audio

In this paper, a unique and transparent data hiding algorithm based on XOR operands triplet (XOT) is proposed. In XOT, an XOR operation applied on any two members of a triplet provides the third member of the same triplet. Taking advantage of the low computational complexity and fascinating properties of the XOR operator, it is possible to embed 4-ary secret digits with negligible changes in the host digital audio. The proposed scheme has been designed to ensure that a minimum number of bit alterations happen in the host digital audio during the data hiding process, which also increases the security of the scheme and provides high quality embedded audio without compromising the statistical property of host audio signals. The scheme confirms that the maximum change is less than 12.5% of the digital audio samples and the average error for the individual digital audio sample is less than 6.25%. The experimental results show that the scheme has a high capacity (88 kbps) without perceptual distortion (objective difference grades are -0.1 to -0.31) and provides robustness against intentional or unintentional attack detection. Comparative analysis shows that our method has better performance than data hiding techniques reported recently in terms of imperceptibility, capacity, and security.

A DWT-Based Rational Dither Modulation Scheme for Effective Blind Audio Watermarking

A scheme jointly exploring the rational dither modulation (RDM) and auditory masking properties in the discrete wavelet transform (DWT) domain is proposed to achieve effective blind audio watermarking. The embedding of binary information is carried out by modulating coefficient vectors in the 5th-level approximation subband using the quantization steps estimated from past watermarked vectors. The robustness and payload capacity of the proposed scheme are maneuverable by varying vector dimensions, while the imperceptibility is ensured by constraining quantization noise below the auditory masking threshold. Furthermore, the periodic characteristic inherited in the RDM formulation can be used to re-establish synchronization for accurate watermark extraction. Experimental results show that the proposed DWT---RDM approach renders a near-zero objective difference grade in the perceptual evaluation of audio quality even when the signal-to-noise ratio maintains at a level near 20 dB. In most digital signal processing attacks, the bit error rates of retrieved watermarks are sufficiently low as compared to other recently developed methods with fewer payload capacities.

A Multi-Level Robust and Perceptually Transparent Blind Audio Watermarking Scheme Using Wavelets

Abstract In this paper, a robust and perceptually transparent single-level and multi-level blind audio watermarking scheme using wavelets is proposed. A randomly generated binary sequence is used as a watermark, and wavelet function coding is used to embed the watermark sequence in audio signals. Multi-level watermarking is used to enhance payload capacity and can be used for a different level of security. The robustness of the scheme is evaluated by applying different attacks such as filtering, sampling rate alteration, compression, noise addition, amplitude scaling, and cropping. The simulation results obtained show that the proposed watermarking scheme is resilient to various attacks except cropping. Perceptual transparency of watermark is measured by using Perceptual Evaluation of Audio Quality (PEAQ) basic model of ITU-R (PEAQ ITU-R BS.1387) on Speech Quality Assessing Material (SQAM) given by European Broadcasting Union (EBU). Average Objective Difference Grade (ODG) measured for this method is -0.067 and -0.080 for single-level and multi-level watermarked audio signals, respectively. In the proposed single-level digital audio watermarking scheme, the payload capacity is increased by 19.05% as compared to the single-level Chirp-Based Digital Audio Watermarking (CB-DAWM) scheme.

HHT-based audio coding

In this paper, a new audio coding scheme combining the Hilbert transform and the empirical mode decomposition (EMD) is introduced. Based on the EMD, the coding is fully a data-driven approach. Audio signal is first decomposed adaptively, by EMD, into intrinsic oscillatory components called intrinsic mode functions (IMFs). The key idea of this work is to code both instantaneous amplitude (IA) and instantaneous frequency (IF), of the extracted IMFs, calculated using Hilbert transform. Since IA (resp. IF) is strongly correlated, it is encoded via a linear prediction technique. The decoder recovers the original signal by superposition of the demodulated IMFs. The proposed approach is applied to audio signals, and the results are compared to those obtained by advanced audio coding (AAC) and MP3 codecs, and wavelets-based compression. Coding performances are evaluated using the bit rate, objective difference grade (ODG) and noise to mask ratio (NMR) measures. Based on the analyzed audio signals, overall, our coding scheme performs better than wavelet compression, AAC and MP3 codecs. Results also show that this new scheme has good coding performances without significant perceptual distortion, resulting in an ODG in range $$[-1,0]$$ and large negative NMR values.